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The resulting.gal files were analyzed by SpotfireDecisionSite, Microarray Analysis module (TIBCO-Spotfire, Boston MA) as previously described [28].
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Briefly, this is a systems-scale strategy for microarray analysis that has identified transcriptional modules formed by genes coordinately expressed across multiple disease data sets thus allowing functional interpretation of the microarray data into biologically useful information.
Our approach goes beyond traditional microarray analysis, because it considers Protein Interaction Network modules as gene groups in a joint differential expression-differential coexpression analysis.
Microarray analysis was done with the SAM module within BRB-Array tools (Version 3.4, NCI).
The microarray analysis does highlight a strong cytokine/growth factor transcriptional module in the CSCs-like bone tropism signature.
Advances in module detection algorithms have elevated microarray analysis to much higher levels than simple identification of differentially expressed genes and Gene Ontology (GO) enrichment analysis.
With recent interest of gene differential coexpression analysis in the gene network or module, gene module analysis has emerged as a novel holistic approach for microarray analysis.
We designed a strategy for microarray analysis that is based on the identification of transcriptional modules formed by genes coordinately expressed in multiple disease data sets.
Among others, there are modules related to phylogenetic analysis, multiple sequence alignment and microarray analysis.
Furthermore to verify the presence of similar binding sites in the promoters of the genes included in individual modules we used the tool PRIMA (PRomoter Integration in Microarray Analysis) [ 29] from the software package EXPANDER [ 30].
Based on the protein microarray analysis, validated in N. benthamiana, AtWRKY53 was phosphorylated when co-expressed with the AtMKK7/AtMPK7 module [ 57].
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